Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 03722, Korea.
Department of Biotechnology, College of Life Science and Biotechnology, Korea University, Seoul 02841, Korea.
Nucleic Acids Res. 2018 Jan 4;46(D1):D380-D386. doi: 10.1093/nar/gkx1013.
Transcription factors (TFs) are major trans-acting factors in transcriptional regulation. Therefore, elucidating TF-target interactions is a key step toward understanding the regulatory circuitry underlying complex traits such as human diseases. We previously published a reference TF-target interaction database for humans-TRRUST (Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining)-which was constructed using sentence-based text mining, followed by manual curation. Here, we present TRRUST v2 (www.grnpedia.org/trrust) with a significant improvement from the previous version, including a significantly increased size of the database consisting of 8444 regulatory interactions for 800 TFs in humans. More importantly, TRRUST v2 also contains a database for TF-target interactions in mice, including 6552 TF-target interactions for 828 mouse TFs. TRRUST v2 is also substantially more comprehensive and less biased than other TF-target interaction databases. We also improved the web interface, which now enables prioritization of key TFs for a physiological condition depicted by a set of user-input transcriptional responsive genes. With the significant expansion in the database size and inclusion of the new web tool for TF prioritization, we believe that TRRUST v2 will be a versatile database for the study of the transcriptional regulation involved in human diseases.
转录因子（TFs）是转录调控中的主要反式作用因子。因此，阐明 TF-靶标相互作用是理解人类疾病等复杂性状的调控回路的关键步骤。我们之前发表了一个人类转录因子-靶标互作参考数据库-TRRUST（基于句子的文本挖掘揭示的转录调控关系），该数据库是通过基于句子的文本挖掘，然后进行人工注释构建的。在这里，我们展示了 TRRUST v2（www.grnpedia.org/trrust），与上一版本相比有了显著的改进，包括数据库的规模显著增加，包含了 800 个人类 TF 的 8444 个调控相互作用。更重要的是，TRRUST v2 还包含了一个用于小鼠 TF-靶标相互作用的数据库，包括 828 个小鼠 TF 的 6552 个 TF-靶标相互作用。TRRUST v2 也比其他 TF-靶标相互作用数据库更全面，偏差更小。我们还改进了网页界面，现在可以根据用户输入的一组转录响应基因，对特定生理条件下的关键 TF 进行优先级排序。随着数据库规模的显著扩大和新的 TF 优先级排序网络工具的纳入，我们相信 TRRUST v2 将成为研究人类疾病相关转录调控的多功能数据库。
